Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

Irina Schelkanova; Vladislav Toronov

doi:10.1117/12.889745

14 June 2011 Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

Irina Schelkanova, Vladislav Toronov

Author Affiliations +

Proceedings Volume 8088, Diffuse Optical Imaging III; 80881M (2011) https://doi.org/10.1117/12.889745
Event: European Conferences on Biomedical Optics, 2011, Munich, Germany

Abstract

Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

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Irina Schelkanova and Vladislav Toronov "Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data", Proc. SPIE 8088, Diffuse Optical Imaging III, 80881M (14 June 2011); https://doi.org/10.1117/12.889745

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